Update app.py

app.py

@@ -1,52 +1,17 @@
-"""Deploying AI Voice Chatbot Gradio App."""
-from gradio import Audio, Interface, Textbox
+import gradio as gr
 
-from utils import (TextGenerationPipeline, from_en_translation,
-                   html_audio_autoplay, stt, to_en_translation, tts,
-                   tts_to_bytesio)
+from transformers import pipeline
 
-max_answer_length = 100
-desired_language = "de"
-response_generator_pipe = TextGenerationPipeline(max_length=max_answer_length)
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-en-es")
 
+def predict(text):
+  return pipe(text)[0]["translation_text"]
 
-def main(audio: object):
-    """Calls functions for deploying gradio app.
-    It responds both verbally and in text
-    by taking voice input from user.
-    Args:
-        audio (object): recorded speech of user
-    Returns:
-        tuple containing
-        - user_speech_text (str) : recognized speech
-        - bot_response_de (str) : translated answer of bot
-        - bot_response_en (str) : bot's original answer
-        - html (object) : autoplayer for bot's speech
-    """
-    user_speech_text = stt(audio, desired_language)
-    tranlated_text = to_en_translation(user_speech_text, desired_language)
-    bot_response_en = response_generator_pipe(tranlated_text)
-    bot_response_de = from_en_translation(bot_response_en, desired_language)
-    bot_voice = tts(bot_response_de, desired_language)
-    bot_voice_bytes = tts_to_bytesio(bot_voice)
-    html = html_audio_autoplay(bot_voice_bytes)
-    return user_speech_text, bot_response_de, bot_response_en, html
+iface = gr.Interface(
+  fn=predict, 
+  inputs='text',
+  outputs='text',
+  examples=[["Hello! My name is Omar"]]
+)
 
-
-Interface(
-    fn=main,
-    inputs=[
-        Audio(
-            source="microphone",
-            type="filepath",
-        ),
-    ],
-    outputs=[
-        Textbox(label="You said: "),
-        Textbox(label="AI said: "),
-        Textbox(label="AI said (English): "),
-        "html",
-    ],
-    live=True,
-    allow_flagging="never",
-).launch()
+iface.launch()